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Mosharaf MP, Alam K, Gow J, Mahumud RA, Mollah MNH. Common molecular and pathophysiological underpinnings of delirium and Alzheimer's disease: molecular signatures and therapeutic indications. BMC Geriatr 2024; 24:716. [PMID: 39210294 PMCID: PMC11363673 DOI: 10.1186/s12877-024-05289-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/20/2024] [Accepted: 08/07/2024] [Indexed: 09/04/2024] Open
Abstract
BACKGROUND Delirium and Alzheimer's disease (AD) are common causes of cognitive dysfunction among older adults. These neurodegenerative diseases share a common and complex relationship, and can occur individually or concurrently, increasing the chance of permanent mental dysfunction. However, the common molecular pathophysiology, key proteomic biomarkers, and functional pathways are largely unknown, whereby delirium is superimposed on AD and dementia. METHODS We employed an integrated bioinformatics and system biology analysis approach to decipher such common key proteomic signatures, pathophysiological links between delirium and AD by analyzing the gene expression data of AD-affected human brain samples and comparing them with delirium-associated proteins. The present study identified the common drug target hub-proteins examining the protein-protein interaction (PPI) and gene regulatory network analysis. The functional enrichment and pathway analysis was conducted to reveal the common pathophysiological relationship. Finally, the molecular docking and dynamic simulation was used to computationally identify and validate the potential drug target and repurposable drugs for delirium and AD. RESULTS We detected 99 shared differentially expressed genes (sDEGs) associated with AD and delirium. The sDEGs-set enrichment analysis detected the transmission across chemical synapses, neurodegeneration pathways, neuroinflammation and glutamatergic signaling pathway, oxidative stress, and BDNF signaling pathway as the most significant signaling pathways shared by delirium and AD. The disease-sDEGs interaction analysis highlighted the other disease risk factors with delirium and AD development and progression. Among the sDEGs of delirium and AD, the top 10 hub-proteins including ALB, APP, BDNF, CREB1, DLG4, GAD1, GAD2, GFAP, GRIN2B and GRIN2A were found by the PPI network analysis. Based on the maximum molecular docking binding affinities and molecular dynamic simulation (100 ns) results, the ALB and GAD2 were found as prominent drug target proteins when tacrine and donepezil were identified as potential drug candidates for delirium and AD. CONCLUSION The study outlined the common key biomolecules and biological pathways shared by delirium and AD. The computationally reported potential drug molecules need a deeper investigation including clinical trials to validate their effectiveness. The outcomes from this study will help to understand the typical pathophysiological relationship between delirium and AD and flag future therapeutic development research for delirium.
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Affiliation(s)
- Md Parvez Mosharaf
- School of Business, Faculty of Business, Education, Law and Arts, University of Southern Queensland, Toowoomba, QLD, 4350, Australia.
- Bioinformatics Lab, Department of Statistics, University of Rajshahi, Rajshahi, 6205, Bangladesh.
| | - Khorshed Alam
- School of Business, Faculty of Business, Education, Law and Arts, University of Southern Queensland, Toowoomba, QLD, 4350, Australia
- Centre for Health Research, University of Southern Queensland, Toowoomba, QLD, 4350, Australia
| | - Jeff Gow
- School of Business, Faculty of Business, Education, Law and Arts, University of Southern Queensland, Toowoomba, QLD, 4350, Australia
- School of Accounting, Economics and Finance, University of KwaZulu-Natal, Durban, 4000, South Africa
| | - Rashidul Alam Mahumud
- School of Business, Faculty of Business, Education, Law and Arts, University of Southern Queensland, Toowoomba, QLD, 4350, Australia
- Health Economics and Health Technology Assessment Unit, NHMRC Clinical Trials Centre, Faculty of Medicine and Health, The University of Sydney, Camperdown, NSW, 2006, Australia
| | - Md Nurul Haque Mollah
- Bioinformatics Lab, Department of Statistics, University of Rajshahi, Rajshahi, 6205, Bangladesh
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Yan M, Lin Z, Zheng H, Lai J, Liu Y, Lin Z. Development of an individualized model for predicting postoperative delirium in elderly patients with hepatocellular carcinoma. Sci Rep 2024; 14:11716. [PMID: 38777824 PMCID: PMC11111779 DOI: 10.1038/s41598-024-62593-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/11/2024] [Accepted: 05/20/2024] [Indexed: 05/25/2024] Open
Abstract
Postoperative delirium (POD) is a common complication in older patients with hepatocellular carcinoma (HCC) that adversely impacts clinical outcomes. We aimed to evaluate the risk factors for POD and to construct a predictive nomogram. Data for a total of 1481 older patients (training set: n=1109; validation set: n=372) who received liver resection for HCC were retrospectively retrieved from two prospective databases. The receiver operating characteristic (ROC) curve, calibration plot, and decision curve analysis (DCA) were used to evaluate the performance. The rate of POD was 13.3% (148/1109) in the training set and 16.4% (61/372) in the validation set. Multivariate analysis of the training set revealed that factors including age, history of cerebrovascular disease, American Society of Anesthesiologists (ASA) classification, albumin level, and surgical approach had significant effects on POD. The area under the ROC curves (AUC) for the nomogram, incorporating the aforementioned predictors, was 0.798 (95% CI 0.752-0.843) and 0.808 (95% CI 0.754-0.861) for the training and validation sets, respectively. The calibration curves of both sets showed a degree of agreement between the nomogram and the actual probability. DCA demonstrated that the newly established nomogram was highly effective for clinical decision-making. We developed and validated a nomogram with high sensitivity to assist clinicians in estimating the individual risk of POD in older patients with HCC.
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Affiliation(s)
- Mingfang Yan
- Department of Anesthesiology, Clinical Oncology School of Fujian Medical University &, Fujian Cancer Hospital, Fuzhou, 350014, Fujian, China
| | - Zhaoyan Lin
- College of Animal Science, Fujian Agriculture and Forestry University, Fuzhou, 350002, Fujian, China
| | - Huizhe Zheng
- Department of Anesthesiology, Clinical Oncology School of Fujian Medical University &, Fujian Cancer Hospital, Fuzhou, 350014, Fujian, China
| | - Jinglan Lai
- Department of Infectious Diseases, Mengchao Hepatobiliary Hospital of Fujian. Medical University, Fuzhou, 350025, Fujian, China
| | - Yuming Liu
- Department of Anesthesiology, Mengchao Hepatobiliary Hospital of Fujian. Medical University, Fuzhou, 350025, Fujian, China.
| | - Zhenmeng Lin
- Department of Anesthesiology, Clinical Oncology School of Fujian Medical University &, Fujian Cancer Hospital, Fuzhou, 350014, Fujian, China.
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Abstract
PURPOSE OF REVIEW Perioperative neurocognitive disorders (PNDs) are among the most frequent complications after surgery and are associated with considerable morbidity and mortality. We analysed the recent literature regarding risk assessment of PND. RECENT FINDINGS Certain genetic variants of the cholinergic receptor muscarinic 2 and 4, as well as a marked degree of frailty but not the kind of anaesthesia (general or spinal) are associated with the risk to develop postoperative delirium (POD). Models predict POD with a discriminative power, for example, area under the receiver operating characteristics curve between 0.52 and 0.94. SUMMARY Advanced age as well as preexisting cognitive, functional and sensory deficits remain to be the main risk factors for the development of PND. Therefore, aged patients should be routinely examined for both preexisting and new developing deficits, as recommended in international guidelines. Appropriate tests should have a high discrimination rate, be feasible to be administered by staff that do not require excessive training, and only take a short time to be practical for a busy outpatient clinic. Models to predict PND, should be validated appropriately (and externally if possible) and should not contain a too large number of predictors to prevent overfitting of models.
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